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All Journal Transcendent Journal of Mathematics and Applications Limits: Journal of Mathematics and Its Applications
Rosidha, Anisa Nur
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Computer Science & IT Economics, Econometrics & Finance Environmental Science Mathematics Physics

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Improved Particle Swarm Optimization in Nutrition Adjustment for Hypertension Patient Rosidha, Anisa Nur; Mardianto, Lutfi; Saputra, Ilham; Nasution, Achmad Suryadi
Transcendent Journal of Mathematics and Applications Vol 3, No 1 (2024)
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/tjoma.v3i1.37791

Abstract

Hypertension is one of the biggest contributors to the death cause in the world. This disease arises due to an unhealthy lifestyle and improper diet. In order to fulfill proper nutrition for people with hypertension, the composition of food for people with this disease needs to be regulated to produce optimal results according to their needs with the Improved Particle Swarm Optimization (IPSO) algorithm. Data collection was carried out on 96 patients with 1000 particles, a maximum iteration of 1000 and acceleration coefficients , , serta . The results show that the best fitness is 6,284 determined by price Rp 28.000 and 14 different variety of food. Based on the tests, the IPSO algorithm is effective in optimizing the nutrition of food composition with an accuracy rate of more than 99%.
Optimasi Komposisi Makanan Penderita Diabetes dengan Hybrid Genetic Algorithm dan Modified Simulated Annealing Nasution, Achmad Suryadi; Saputra, Ilham; Rosidha, Anisa Nur; Mardianto, Lutfi
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 3 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 3 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Diabetes mellitus is one of the deadliest diseases. Factors that can cause diabetes mellitus are irregular eating patterns and unhealthy lifestyles. Patients with diabetes mellitus must have a healthy diet by identifying the optimal food composition so as not to trigger complications with various other deadly diseases. Identification of food composition was carried out using a hybrid adaptive genetic algorithm and modified simulated annealing. Based on the patient testing results, the average accuracy for carbohydrates, protein, fat, sodium, fiber, and calories was 99.90%, 99.72%, 99.33%, 99.99%, 99.29%, and 99.86%, respectively.
Co-Authors Achmad Suryadi Nasution Mardianto, Lutfi Saputra, Ilham